181–190 of 218 posts
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yep. the word they use is probably 克制 or self-restraint. no need to raise so much cash if you can't use it. in his article he talks about the negative aspects of getting everything you want. (all the money, brightest minds, biggest share in AI) etc. he says that these are the things that will cause a company to fail.
I shouldn't win too hard, because then I'll lose?
Here's something I really don't understand: If as alleged Chinese open weight models are catching up with US anyway, and the performance is near US frontier model level but Chinese can do it with a fraction of cost, and eventually AI model will be commodified, wouldn't that means that the billion or even trillion dollars that US labs spend have only diminishing returns and the lead is only temporary? So why Deepseek…
U.S. policymakers believe that even if the gap is small—like six months to a year—whoever reaches AGI first (whatever that means) could gain such an overwhelming advantage over their perceived adversary that it would effectively kneecap them. (You can look at the kinds of things they mention—cyber, WMDs—to get a sense of what they mean.) Jensen Huang disagrees and has said AI is a marathon.
Everyone is trying to figure out how to achieve this prerequisite. I'm thinking of agent harnesses. That's what everyone is trying to do at this point.
That's the same problem I'm trying to solve: https://github.com/rush86999/atom
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Chinese companies are effectively embargoed from using them for <14nm.
Sounds like an invasion of Taiwan could fix that problem for them.
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They would until you showed them the jagged edges. Like those short videos of the guy asking the model to count up to 100, for example, where it politely agrees but never actually gets there
So does AGI just mean infallible?
It’s clearly not actually that “generalized” yet because it’s unable to do a number of very simple things that almost any 6-year old could do, such as count to 100 without using any tools.
It’s still a very specific type of intelligence, with some real breadth to it, but not general intelligence.
Give it 5 years for China to have it's own ASML. Nothing big bang is going to happen in 5 years or even a decade from now, execpt for a few more hypes, deep corrections and the political drama. AGI is not a destination, but a journey. There are no winners.
Are you saying there are no deep corrections and the political drama in China?
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Maybe: "Leaked Deepseek transcripts reveal plan to pause fundraising due to compute gap" I don't know what "compute gap" means in this context though and it's not clear that that's why they plan to pause fundraising or if the title is conflating.
yep. the word they use is probably 克制 or self-restraint. no need to raise so much cash if you can't use it. in his article he talks about the negative aspects of getting everything you want. (all the money, brightest minds, biggest share in AI) etc. he says that these are the things that will cause a company to fail.
Here's something I really don't understand: If as alleged Chinese open weight models are catching up with US anyway, and the performance is near US frontier model level but Chinese can do it with a fraction of cost, and eventually AI model will be commodified, wouldn't that means that the billion or even trillion dollars that US labs spend have only diminishing returns and the lead is only temporary? So why Deepseek…
They are not catching up to US models. The only Chinese models that attain a modicum of competence are all, sooner or later, are discovered to be trained by exploiting US models (in fact Deepseek itself admitted so about 1 year back). Chinese models are not innovating anything, they are just doing what China does everywhere else: copying the West… poorly but cheaper.
Whether they get there by distillation, or by pirating all content themselves just like the US labs, doesn't matter for the topic at hand.
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It's understood that LLMs have limitations and people are working on "the next thing" to try and make it to real AGI, e.g. Yann LeCun.
Many people have tried before, but the bitter lesson has come for them all.
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I wonder if it would be viable for the Chinese to pursue a huge buildout of less sophisticated logic fabs. My experience with GPGPU is that it seems to intensely skew towards memory bandwidth, and has a much lower compute intensity than graphics (by which I mean rasterization and shaders). This seems to be holding true for AI as well. I'm sure if you have an excess of compute and a dearth of bandwidth, you can trade…
The real question is whether it's easier to improve the software side instead. There are likely a lot more optimizations possible in terms of model architecture, and if there is a compute bottleneck, then it's going to put a lot of pressure on Chinese labs to address the problem using more efficient designs.